4 papers
Beyond Compression: Training Latent Representations for Stable Long-Horizon Rollout in Neural Surrogate Solvers
Andreas E. Robertson, Ashley T. Lenau, John D. Shimanek +5
Latent neural surrogate solvers, or latent dynamics models, accelerate simulations of time-dependent physical systems by evolving a compressed latent space rather than resolving fu…
Materials Behavior as Mechanism Ensembles: A Probabilistic Framework for Emergent Behaviors
Brad L. Boyce, Mitchell A. Wood, Krishna Garikipati +16
Materials behavior is often treated as a deterministic mapping from structure to properties, yet many important phenomena emerge from the conditional activation of multiple mechani…
Microstructure-based Variational Neural Networks for Robust Uncertainty Quantification in Materials Digital Twins
Andreas E. Robertson, Samuel B. Inman, Ashley T. Lenau +4
Aleatoric uncertainties - irremovable variability in microstructure morphology, constituent behavior, and processing conditions - pose a major challenge to developing uncertainty-r…
Equilibrium Conserving Neural Operators for Super-Resolution Learning
Vivek Oommen, Andreas E. Robertson, Daniel Diaz +5
Neural surrogate solvers can estimate solutions to partial differential equations in physical problems more efficiently than standard numerical methods, but require extensive high-…